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Technical Leader - AIOps & Agentic Platform

  • Source: Workday
  • Cisco
  • $184,300 to $233,200 /yr
  • Remote
  • Full-Time
  • Senior

Job Description

The application window is expected to close on: 12/30/2026

Meet the team

You will join the Cisco Mobility Services organization, part of the Mass-Scale Infrastructure Group (MIG) within Cisco. Cisco IoT Control Center is the #1 best-in-class cellular connectivity management platform, supporting over 300 million connected devices globally across critically important enterprise and telecom networks. Our global organization is responsible for end-to-end engineering and production operations of the platform.

In this role, you will be a key senior engineer and technical leader building our next-generation AIOps and Agentic Operations Platform. You will design and implement AI-powered operational tools and multi-agent systems, actively participate in architectural and system design discussions, and partner closely with architects, SREs, and engineering leads to help our global teams operate complex distributed systems with high reliability, intelligence, and speed.

Your impact

  • Build & scale agentic operations: Design, build, and deliver production-grade AI agents, multi-agent workflows, and platform capabilities that automate and optimize complex SRE and infrastructure operations.
  • Participate in architectural design: Actively contribute to architectural reviews, design specifications, and technical trade-off discussions for agentic platform interfaces, tool integration frameworks (e.g., Model Context Protocol / MCP), and observability pipelines.
  • Autonomous’ incident & anomaly remediation: Develop intelligent operational workflows applying AI/ML, statistical analysis, and causal inference to real-time anomaly detection, automated root-cause analysis (RCA), and proactive incident mitigation.
  • Telemetry & tool integration: Design and implement integrations with existing telemetry frameworks, distributed monitoring systems, APIs, and cloud/on-prem environments to power real-time AI context gathering.
  • Production reliability & guardrails: Implement robust automated testing, evaluation harnesses, human-in-the-loop (HITL) approval gates, and deployment pipelines to ensure deterministic, safe, and secure agent behaviors in production.
  • Cross-team technical leadership: Collaborate closely with Principal Engineers, software engineers, data scientists, and operations teams to integrate AI capabilities smoothly into core platform workflows and mentor team members on AI engineering standard methodologies.
  • Measurable operational outcomes: Measure and report on operational critical metric gains, MTTR reduction, and automation efficiency to continuously refine agent performance and tool capabilities.

Minimum qualifications

  • Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field with 10+ years of relevant software engineering experience, or Master’s degree with 8+ years, or PhD with 5+ years.
  • 8+ years of experience building, testing, and deploying backend software, operational tooling, or platform services within large-scale distributed environments.
  • Proven track record of authoring at least 3+ major design proposals/RFCs and leading system design reviews for complex technical implementations.
  • 5+ years of deep proficiency in Python, Go, Java, or Rust, with demonstrated expertise in concurrency, data structures, and API development.
  • 2+ years of practical experience developing with LLMs, including documented success in prompt engineering, tool/function calling, or transitioning AI agents from prototype to production.

Preferred qualifications

  • Experience with modern agent orchestration, semantic search, retrieval-augmented generation (RAG), and standard tool integration interfaces (e.g., MCP, function schemas).
  • Experience working with distributed telemetry and data pipelines (e.g., OpenTelemetry, Prometheus, Kafka/Pulsar, Elasticsearch, Vector Databases).
  • Practical exposure to SRE practices, CI/CD automation, Kubernetes/container environments, and runbook orchestration.
  • Experience building evaluation benchmarks, structured output validation, or security guardrails for production AI systems.

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work toget…

Skills

  • guardrails
  • Python
  • Golang
  • Java
  • rust
  • opentelemetry
  • Prometheus
  • Kafka
  • pulsar
  • Elasticsearch
  • vector
  • Kubernetes
  • runbook
  • fullcalendar
  • workday

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